Statistical Analyses of Multilocation Trials

Abstract

This chapter presents the statistical analysis of multilocation trials. Multilocation trials play an important role in plant breeding and agronomic research. Data from such trials have three main agricultural objectives—to accurately estimate and predict yield based on limited experimental data; to determine yield stability and the pattern of response of genotypes or agronomic treatments across environments; and to provide reliable guidance for selecting the best genotypes or agronomic treatments for planting in future years and at new sites. Agronomists use multilocation trials to compare combinations of agronomic factors, such as fertilizer levels and plant density, and on this basis make recommendations for farmers. Breeders compare different improved genotypes to identify the superior ones. Data collected in multilocation trials are intrinsically complex, having three fundamental aspects—namely, structural patterns; nonstructural noise; and relationships among genotypes, environments, and genotypes and environments considered jointly. Pattern implies that a number of genotypes respond to certain environments in a systematic, significant, and interpretable manner, whereas noise suggests that the responses are unpredictable and uninterpretable.